Abstract (inglese)

Agent-oriented programming paradigm and mobile software agents are getting the attention of IT community because they look a promising solution for the development of systems that fit the computational requirements of emerging mobile computing, ubiquitous computing and pervasive computing.
Software agents consist of autonomous processes that run on a hosting platform and that are aimed at achieving specific owners' goals they were programmed for.
Agents can migrate from host to host in order to exploit resources and services that are available in the distributed system.

In the 90's, at the beginning of the agent model definition and development, agent systems addressed applications with strictly local perspectives: the whole system was contained within a defined boundary and was composed of a defined set of known agents and hosts.
Agent systems are now moving towards open perspective applications: agent platforms are involving in wide size and higly dynamic distributed systems without well-defined boundaries.

Security issues that arise in open agent systems require new protection mechanisms that combine the protection from malicious agents with local boundaries that are open to the community of users.
Soft security mechanisms are based on the employment of trust and reputation concepts that are derived from the same definitions used in social relationships.
Soft security is employed in trust-based decision making: it support the evaluation of risks that are involved in interactions with unknown agents; reputation information informs agents about the behavior and honesty of agents in the community according to the opinions coming from experienced interactions.

We propose a model for reputation management that is compliant with the characteristics of the agent systems (e.g. dynamicity of agents), and that meets also requirements that arise in these systems in critical situations, e.g. low computational power in small portable devices that host agents and low and unstable communication bandwidth in mobile devices.

The model is based on the evaluation of opinions that are collected within context groups.
A context group is a coalition of agents that provide opinions related to the behaviors of agents. In a context group opinions are related to a specific context.
Hence the proposed model introduces a context feature to reputation information.
The reputation model provides agents with information that regards both the general fairness of an agent and its behavior related to the context where it is rated.

The model is also composed of a network of distributed informative points that are aimed at supporting trust information sharing among context groups.

The model is consistent for what concerns both the agent model and the agent social perspective because its design adopted an agent-centric approach but at the same time it adopted solutions in order to employ the model in large society of agents.